Enterprises that manufacture, sell or support products typically maintain information processing systems for storing reliability data regarding their products. For example, failure rates for various products may be stored and tracked over time in order to facilitate implementation of various product improvements and to coordinate other related functions such as customer support and product recalls.
Conventional approaches to product reliability analysis in such systems suffer from a number of significant drawbacks. For example, many of these approaches are unable to handle the high-dimensionality data that can result from large numbers of possible product and part combinations. Other approaches fail to provide sufficient specificity of predicted outcomes in the case of relatively sparse data and are therefore unsuitable for use in early detection of reliability issues.